Project summary (<30 lines) Dysfunction of both the hippocampus and the orbitofrontal cortex have been implicated in a wide variety of neuropsychiatric disorders, including obsessive-compulsive disorder, mood disorders and addiction. However, their exact contribution remains unclear. A major problem is that most research on hippocampal mechanisms is derived from rodent work. However, the structure of the hippocampus has undergone dramatic changes across the course of evolution, particularly in those parts associated with psychopathologies. This necessitates the use of primate models, but there have been few studies of hippocampus in the primate. The current grant will investigate the neuronal properties of hippocampus in the primate and determine how it interacts with orbitofrontal cortex. The theoretical framework that we will employ is derived from computational psychiatry, with a particular focus on how the computational processes underlying reinforcement learning might contribute to neuropsychiatric disease. Our hypothesis is that both hippocampus and orbitofrontal cortex make critical contributions to model-based reinforcement learning, whereby hippocampus is responsible for constructing the cognitive map that instantiates the neural representation of the task model, and orbitofrontal cortex is responsible for using the cognitive map to generate reward predictions that can be used to guide decision-making. To test this hypothesis, we will use a combination of high-channel count neuronal recordings and electrical microstimulation. We will record from single neurons in the hippocampus during performance of a reward-based learning task and examine whether hippocampal neurons show value place tuning. We will then examine how hippocampus might communicate this information to orbitofrontal cortex by recording from both structures simultaneously. Our prediction is that this communication will be mediated via synchronization of theta rhythms. However, such measures are correlative. Establishing a causal role for neural rhythms has proven challenging, since it is difficult to manipulate a specific neuronal rhythm without affecting other neuronal rhythms and/or neuronal firing rates. We have recently developed a closed-loop approach, which involves recording rhythms in real-time and using those signals to control the application of electrical microstimulation. This allows us to disrupt a neuronal rhythm of a specific frequency. We will use this method to examine whether there is a causal role for the theta oscillation in reward-based learning. Taken together, the results of this proposal will provide convergent correlative and causal evidence for the role of hippocampus and orbitofrontal cortex in reward-based learning and the mechanism by which they communicate. This will help lay the groundwork for future potential therapeutic approaches for frontolimbic dysfunction based on closed-loop microstimulation.